XI International Symposium on Vulcanospeleology, Pico Island, Azores, May 12-18, 2004. | All Azorean lava-tubes and volcanic pits with fauna were evaluated for species diversity and rarity based on arthropods. To produce an unbiased multiple-criteria index (importance value for conservation, IV-C) incorporating arthropod species diversity based indices and indices qualifying geological and management features (e.g. diversity of geological structures, threats, accessibility, etc.), an iterative partial multiple regression analysis was performed. In addition, the complementarity method (using heuristic methods) was used for priority-cave analyses. Most hypogean endemic species have restricted distributions, occurring only in one cave. It was concluded that several well-managed protected caves per island are absolutely necessary to have a good fraction of the endemic arthropods preserved. For presence/absence data, suboptimal solutions indicate that at least 50% lava-tubes with known hypogean fauna are needed if we want that 100% of endemic arthropod species are represented in a minimum set of reserves. Based both on the uniqueness of species composition and/or high species richness and geological value of the caves, conservation efforts should be focused on the following caves: Gruta da Beira, Algar das Bocas do Fogo (S. Jorge); Montanheiros, Henrique Maciel, Soldão, Furna das Cabras II and Ribeira do Fundo (Pico); Algar do Carvão, Balcões, Agulhas and Chocolate (Terceira); Água de Pau (S. Miguel); Anelares and Parque do Capelo (Faial).

The research described in this paper focuses on identification of the most important indicators for emerging mycotoxins, starting from those produced by Fusarium fungi, in wheat-based feed and food supply chains, as well as the development of a conceptual model to predict the occurrence of these emerging toxins, based on the selected indicators. The selection of the most important indicators was based on a literature review and evaluation of the resulting indicators for their relevance. Each indicator selected was appointed to relevant stage(s) of the supply chain to which it is related and, for each indicator, a suggestion for a potential information source is given. The selected indicators cover various influential sectors, amongst others, weather conditions, agronomical practices, trade and legislation, as well as a variety of information sources, e.g. on-farm records and statistical organisations. The conceptual model developed is aimed at predicting the occurrence of emerging mycotoxins – based on the selected indicators – in a particular unit of wheat. The model takes a supply chain approach and can handle various types of indicators and various levels of detail of information on origin of the unit of wheat. The proposed model could be useful in the development of an identification system for emerging risks related to mycotoxins in wheat-based supply chains. Ultimately, such a system will help industry and policy makers in their decision-making process with regard to prevention and control of upcoming risks.

Indicators are the most effective tool for the assessment of environment. National and international organisations deal with indicator evaluation. Evaluation is based on the causal D-P-S-I-R framework adopted by the European Environment Agency: Driving force (D), Pressure (P), State (S), Impact (I), Response (R), what is extension of P-S-R model developed by Organistaion for economic co-operation and developmaent. Evaluation based on environmental indicators according to D-P-S-I-R model was implemented also in Slovakia. There were set up 46 agri-environmental indicators according to analyses of EEA, OECD, Eurostat and UN indicators. Indicators are yearly updated. They are unic in structure and include descirption, trends, political objectives, interantional comaprision, references. Indicators are base for indicator reports. Indicators and reports are available on the environment portal Enviroportal which enables interactions between them.

Co-adaptive management of biodiversity is largely based on a collective learning process. This collective learning concerns "instrumental policy learning," "social policy learning," and " political learning." This paper focuses on instrumental policy learning that has been launched in four West African biosphere reserves. It is based on a MAB-UNESCO/UNEP-GEF programme concerning the co-construction of interaction indicators (between development and conservation), inspired by the Integrated Natural Resource Management (INRM) methodology. Using this process, we were able to test conventional Pressure-State-Response indicators, highlight their limitations, and develop new indicators starting from stakeholders' stories and perceptions. These new indicators can also be tested through collective restitutions and simulations. We also discuss: a proposed framework for producing interaction indicators that are relevant to all stakeholders and enjoy a certain legitimacy; the importance of an ecosystem services approach to support discussions on biodiversity conservation; opportunities for using the indicators in an interactive, decentralized way at the ecosystem scale through simulation models; the costs of collecting, processing, and maintaining these interaction indicators, and how these costs may be offset using local knowledge.

Co-adaptive management of biodiversity is largely based on a collective learning process. This collective learning concerns "instrumental policy learning," "social policy learning," and "political learning." This paper focuses on instrumental policy learning that has been launched in four West African biosphere reserves. It is based on a MAB-UNESCO/UNEP-GEF programme concerning the co-construction of interaction indicators (between development and conservation), inspired by the Integrated Natural Resource Management (INRM) methodology. Using this process, we were able to test conventional Pressure-State-Response indicators, highlight their limitations, and develop new indicators starting from stakeholders' stories and perceptions. These new indicators can also be tested through collective restitutions and simulations. We also discuss: a proposed framework for producing interaction indicators that are relevant to all stakeholders and enjoy a certain legitimacy; the importance of an ecosystem services approach to support discussions on biodiversity conservation; opportunities for using the indicators in an interactive, decentralized way at the ecosystem scale through simulation models; the costs of collecting, processing, and maintaining these interaction indicators, and how these costs may be offset using local knowledge.

Environmental impacts of agriculture cannot be always assessed by using direct measurements. Since the 1990s, numerous agri-environmental indicators were developed to assess the adverse effects of cropping and farming systems in the environment, such as water pollution, soil erosion, and emission of greenhouse gases. Here we present the different types of indicators developed during the last decade and review the progress of the methods used for their development. The application of different groups of indicators is discussed and illustrated by examples in the fields of nitrogen losses and pesticide risk: (1) indicators based on a single or a combination of variables related to farmer practices, (2) indicators derived from operational or more complex simulation models assessing emissions of pollutants, and (3) measured indicators linked directly to environmental impacts. The nitrogen indicator (IN) of the INDIGO method and the MERLIN indicator will be presented and used to illustrate the methodological discussion. We show that a good identification of the end-users, of the practical objectives of the indicator, and of the spatial and temporal scales is essential and should be done at a preliminary step before designing the indicator itself. The possibilities of deriving an indicator from a model and of setting a reference value are discussed. Several methods are also presented to study the sensitivity and the validity of agri-environmental indicators. Finally, several practical recommendations are made. As only few data are usually available at the regional level, several simple indicators should be used for assessing a given impact at this level. When more detailed information is available, indicators based on operational models can be useful to analyse the effects of several factors related to soil, climate, and cropping system on an environmental impact. In experimental studies, we suggest using both measured indicators and model-based indicators.

Environmental impacts of agriculture cannot be always assessed by using direct measurements. Since the 1990s, numerous agri-environmental indicators were developed to assess the adverse effects of cropping and farming systems in the environment, such as water pollution, soil erosion, and emission of greenhouse gases. Here we present the different types of indicators developed during the last decade and review the progress of the methods used for their development. The application of different groups of indicators is discussed and illustrated by examples in the fields of nitrogen losses and pesticide risk: (1) indicators based on a single or a combination of variables related to farmer practices, (2) indicators derived from operational or more complex simulation models assessing emissions of pollutants, and (3) measured indicators linked directly to environmental impacts. The nitrogen indicator (IN) of the INDIGO method and the MERLIN indicator will be presented and used to illustrate the methodological discussion. We show that a good identification of the end-users, of the practical objectives of the indicator, and of the spatial and temporal scales is essential and should be done at a preliminary step before designing the indicator itself. The possibilities of deriving an indicator from a model and of setting a reference value are discussed. Several methods are also presented to study the sensitivity and the validity of agri-environmental indicators. Finally, several practical recommendations are made. As only few data are usually available at the regional level, several simple indicators should be used for assessing a given impact at this level. When more detailed information is available, indicators based on operational models can be useful to analyse the effects of several factors related to soil, climate, and cropping system on an environmental impact. In experimental studies, we suggest using both measured indicators and model-based indicators.

During the last 20 years, numerous agro-environmental indicators have been developed and combined into models to assess the impact of livestock on biodiversity and to monitor agro-environmental policies. Surprisingly, most studies on indicators do not explicitly mention accuracy and cost as desirable properties. This paper reports the results of a study aimed at (i) measuring the accuracy and cost of a wide range of indicators combined into models for the assessment of livestock impact on biodiversity and (ii) discussing their usefulness on the basis their cost and accuracy. Nine model selection procedures (MS) and two cross validation techniques (CV) were used to combine two types of biodiversity indicators (stocking rate and sward characteristic) measured on 252 grazed plots during two years. Sensitivity, specificity, and probability of correctly ranking plots were estimated for each model. Results showed that MS and CV had low influence on accuracy. Accuracy and cost of models were mainly influenced by the type of indicators. Models based on stocking rate indicators only were less accurate (-8%) than those based on sward characteristics but they had the lowest cost (531 versus 2495 €) with a satisfactory discriminatory ability (c. 75%). This statistical method could support researchers, farm advisers, and decision makers in comparing various indicators.

During the last 20 years, numerous agro-environmental indicators have been developed and combined into models to assess the impact of livestock on biodiversity and to monitor agro-environmental policies. Surprisingly, most studies on indicators do not explicitly mention accuracy and cost as desirable properties. This paper reports the results of a study aimed at (i) measuring the accuracy and cost of a wide range of indicators combined into models for the assessment of livestock impact on biodiversity and (ii) discussing their usefulness on the basis their cost and accuracy. Nine model selection procedures (MS) and two cross validation techniques (CV) were used to combine two types of biodiversity indicators (stocking rate and sward characteristic) measured on 252 grazed plots during two years. Sensitivity, specificity, and probability of correctly ranking plots were estimated for each model. Results showed that MS and CV had low influence on accuracy. Accuracy and cost of models were mainly influenced by the type of indicators. Models based on stocking rate indicators only were less accurate (-8%) than those based on sward characteristics but they had the lowest cost (531 versus 2495 €) with a satisfactory discriminatory ability (c. 75%). This statistical method could support researchers, farm advisers, and decision makers in comparing various indicators.

Results show that during 1982-2005, gross domestic product of agriculture, manufacturing and all sectors have been rising continuously. All environmental conservation indicators have been also rising but environmental quality indicators have been differentiated. The analysis of relationship between economic growth and the environment, based on EKC using simple environmental index showed that each sectoral growth had positive relationship with the environmental conservation indicators. However, the relationship between economic growth and the environmental quality indicators were mostly negative. In the part of the relationship between economic growth and the environment of Thailand based on EKC using composite environmental index showed that gross domestic product of agriculture, manufacturing and all sectors had positive relationship with environmental conservation indicators were positive, contrary, the relationships between all sectors and the environmental quality indicators were negative. The analysis results of Cobb - Douglas production function showed that some environmental conservation indicators and environmental quality indicators had negative effect on economic growth. This study recommends that there should be more specific for natural resource protection and rehabilitation with emphasis on mangrove forest. Specific measure for controlling wastewater in agricultural sector and air pollution in manufacturing and all sectors, and hazardous waste management in all sectors should be more concerned.